Comprehensive gene expression profiling and immunohistochemical studies support application of immunophenotypic algorithm for molecular subtype classification in diffuse large B-cell lymphoma: A report from the International DLBCL Rituximab-CHOP Consortium Program Study Academic Article uri icon

Overview

MeSH Major

  • Algorithms
  • Antineoplastic Combined Chemotherapy Protocols
  • Biomarkers, Tumor
  • Gene Expression Profiling
  • Lymphoma, Large B-Cell, Diffuse

abstract

  • Gene expression profiling (GEP) has stratified diffuse large B-cell lymphoma (DLBCL) into molecular subgroups that correspond to different stages of lymphocyte development-namely germinal center B-cell like and activated B-cell like. This classification has prognostic significance, but GEP is expensive and not readily applicable into daily practice, which has lead to immunohistochemical algorithms proposed as a surrogate for GEP analysis. We assembled tissue microarrays from 475 de novo DLBCL patients who were treated with rituximab-CHOP chemotherapy. All cases were successfully profiled by GEP on formalin-fixed, paraffin-embedded tissue samples. Sections were stained with antibodies reactive with CD10, GCET1, FOXP1, MUM1 and BCL6 and cases were classified following a rationale of sequential steps of differentiation of B cells. Cutoffs for each marker were obtained using receiver-operating characteristic curves, obviating the need for any arbitrary method. An algorithm based on the expression of CD10, FOXP1 and BCL6 was developed that had a simpler structure than other recently proposed algorithms and 92.6% concordance with GEP. In multivariate analysis, both the International Prognostic Index and our proposed algorithm were significant independent predictors of progression-free and overall survival. In conclusion, this algorithm effectively predicts prognosis of DLBCL patients matching GEP subgroups in the era of rituximab therapy.

authors

publication date

  • September 2012

Research

keywords

  • Academic Article

Identity

Language

  • eng

PubMed Central ID

  • PMC3637886

Digital Object Identifier (DOI)

  • 10.1038/leu.2012.83

PubMed ID

  • 22437443

Additional Document Info

start page

  • 2103

end page

  • 13

volume

  • 26

number

  • 9